Forecast modelling for rotations of principal axes of multidimensional data sets

Huiwen Wang; Qiang Liu

doi:10.1016/s0167-9473(98)00008-5

Forecast modelling for rotations of principal axes of multidimensional data sets

Huiwen Wang^*
, Qiang Liu

^*此作品的通讯作者

科研成果: 期刊稿件 › 文章 › 同行评审

4 引用（Scopus）

摘要

A set of principal axes accounts for the largest variation directions of a data set. It is one of the important general features of the data set. The paper discusses the forecast modelling method for the rotation of principal axes in the multidimensional space. The method was used in forecasting and analysing the development of city economy in China. The movement direction of the main features of the economic development of the city group can be predicted.

源语言	英语
页（从-至）	345-354
页数	10
期刊	Computational Statistics and Data Analysis
卷	27
期	3
DOI	https://doi.org/10.1016/s0167-9473(98)00008-5
出版状态	已出版 - 1 5月 1998

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 8 体面工作和经济增长

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10.1016/s0167-9473(98)00008-5

其它文件与链接

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引用此

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title = "Forecast modelling for rotations of principal axes of multidimensional data sets",

abstract = "A set of principal axes accounts for the largest variation directions of a data set. It is one of the important general features of the data set. The paper discusses the forecast modelling method for the rotation of principal axes in the multidimensional space. The method was used in forecasting and analysing the development of city economy in China. The movement direction of the main features of the economic development of the city group can be predicted.",

keywords = "Forecasting, Multidimensional data set, Principal axes, matrix rotation decomposing",

author = "Huiwen Wang and Qiang Liu",

year = "1998",

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T1 - Forecast modelling for rotations of principal axes of multidimensional data sets

AU - Wang, Huiwen

AU - Liu, Qiang

PY - 1998/5/1

Y1 - 1998/5/1

N2 - A set of principal axes accounts for the largest variation directions of a data set. It is one of the important general features of the data set. The paper discusses the forecast modelling method for the rotation of principal axes in the multidimensional space. The method was used in forecasting and analysing the development of city economy in China. The movement direction of the main features of the economic development of the city group can be predicted.

AB - A set of principal axes accounts for the largest variation directions of a data set. It is one of the important general features of the data set. The paper discusses the forecast modelling method for the rotation of principal axes in the multidimensional space. The method was used in forecasting and analysing the development of city economy in China. The movement direction of the main features of the economic development of the city group can be predicted.

KW - Forecasting

KW - Multidimensional data set

KW - Principal axes, matrix rotation decomposing

UR - https://www.scopus.com/pages/publications/0032071837

U2 - 10.1016/s0167-9473(98)00008-5

DO - 10.1016/s0167-9473(98)00008-5

M3 - 文章

AN - SCOPUS:0032071837

SN - 0167-9473

VL - 27

SP - 345

EP - 354

JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

IS - 3

ER -

Forecast modelling for rotations of principal axes of multidimensional data sets

摘要

联合国可持续发展目标

访问文件

其它文件与链接

指纹

引用此